Multi-objective genetic algorithm for energy-efficient job shop scheduling

Gökan May, Bojan Stahl, Marco Taisch, Vittal Prabhu

Research output: Contribution to journalArticlepeer-review

199 Scopus citations


The paper investigates the effects of production scheduling policies aimed towards improving productive and environmental performances in a job shop system. A green genetic algorithm allows the assessment of multi-objective problems related to sustainability. Two main considerations have emerged from the application of the algorithm. First, the algorithm is able to achieve a semi-optimal makespan similar to that obtained by the best of other methods but with a significantly lower total energy consumption. Second, the study demonstrated that the worthless energy consumption can be reduced significantly by employing complex energy-efficient machine behaviour policies.

Original languageEnglish (US)
Pages (from-to)7071-7089
Number of pages19
JournalInternational Journal of Production Research
Issue number23
StatePublished - Dec 2 2015

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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